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A numerical study on the sound radiation by turbulent jets based on a wavepacket sound-source model

Grant number: 21/12698-9
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): January 01, 2022
Effective date (End): December 31, 2022
Field of knowledge:Engineering - Aerospace Engineering
Principal researcher:Carlos do Carmo Pagani Júnior
Grantee:Guilherme Lellis Cuellar
Home Institution: FAC ENGENHARIA SAO JOAO BOA VISTA/UNESP

Abstract

Spatially coherent and organized flow structures produced by turbulent jets have been recognized as efficient sound generation mechanisms with characteristic directivity patterns. Considerations based on Lighthill's acoustic analogy, as well as in experimental observations and numerical simulations, underpin the use of an axially-extended stochastic line-source based on a linear Gaussian wave packet model to describe the far-acoustic field, produced by turbulent jets, in terms of axisymmetric azimuthal Fourier modes. The acoustic model backbone relies on using the inhomogeneous wave equation to relate the hydrodynamic flow field to the sound pressure field by means of a frequency-domain convolution integral. The sound field related to the wavepacket-based line-source model is numerically resolved in the framework of the resolvent analysis applied to a stochastic system, which is suitable for the treatment of relevant jet noise features in both subsonic and supersonic convective Mach numbers. In this research proposal, we intend to accomplish the computational implementation and numerical simulation of an axially-coherent, noncompact, line-source model, which has been shown to be able of reproducing, with good approximation, the axisymmetric azimuthal Fourier modes of the sound field generated by turbulent jets. A parametric study will be conducted to numerically investigate the relevant features of the radiated sound field, such as the shape of radiation and super directivity at subsonic Mach number. The acoustic field will be sampled by an array of virtual microphones and the results will be preferentially presented in the frequency domain. In addition to simulating the acoustic field produced by turbulent jets within a wide range of sound-source parameters and experimental conditions, this work aims to compile a comprehensive database suitable for supporting the development and training of a machine-learning algorithm to be applied in the recognition of relevant characteristics of turbulent jet noise sources.(AU)

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